Bryan Tipán

Graph Neural Networks with dilated convolutions for geomagnetic field forecasting: a single-station topological approach

It is shown that high-frequency fluctuations at a single station are dominated by instrumental and stochastic noise, making temporal filtering via downsampling essential, and utilizing a learned adjacency matrix as an adaptable structural regularization provides a highly stable and effective framework for short-term geomagnetic field forecasting.